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» Unsupervised Learning of Object Deformation Models
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CVPR
2010
IEEE
15 years 3 months ago
Latent Hierarchical Structural Learning for Object Detection
We present a latent hierarchical structural learning method for object detection. An object is represented by a mixture of hierarchical tree models where the nodes represent objec...
Leo Zhu, Yuanhao Chen, Antonio Torralba, Alan Yuil...
TSMC
2011
292views more  TSMC 2011»
14 years 4 months ago
Circular Blurred Shape Model for Multiclass Symbol Recognition
—In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. ...
Sergio Escalera, Alicia Fornés, Oriol Pujol...
ICPR
2006
IEEE
15 years 11 months ago
Latent Layout Analysis for Discovering Objects in Images
Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
David Liu, Datong Chen, Tsuhan Chen
UAI
2004
14 years 11 months ago
Factored Latent Analysis for far-field Tracking Data
This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...
Chris Stauffer
ISVC
2010
Springer
14 years 7 months ago
Egocentric Visual Event Classification with Location-Based Priors
We present a method for visual classification of actions and events captured from an egocentric point of view. The method tackles the challenge of a moving camera by creating defor...
Sudeep Sundaram, Walterio W. Mayol-Cuevas